Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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Fraud.net
Fraud.net is the world's leading infrastructure for fraud management. It is powered by a sophisticated collective Intelligence network, world-class AI, and a modern cloud-based platform that assists you:
* Combine fraud data from all sources with one connection
* Detect fraudulent activity in real-time for transactions exceeding 99.5%
* Uncover hidden insights in Terabytes of data to optimize fraud management
Fraud.net was recognized in Gartner's market guide for online fraud detection. It is a real-time enterprise-strength, enterprise-strength, fraud prevention and analytics solution that is tailored to the needs of its business customers. It acts as a single point-of-command, combining data from different sources and systems, tracking digital identities and behaviors, then deploying the most recent tools and technologies to eradicate fraudulent activity and allow transactions to go through.
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Watson Natural Language Understanding
Watson Natural Language Understanding is a cloud-native solution that leverages deep learning techniques to derive metadata from text, including entities, keywords, categories, sentiment, emotions, relationships, and syntactic structures. Delve into the topics within your data through text analysis, which enables the extraction of keywords, concepts, categories, and more. The service supports the analysis of unstructured data across over thirteen different languages. With ready-to-use machine learning models for text mining, it delivers a remarkable level of accuracy for your content. You can implement Watson Natural Language Understanding either behind your firewall or on any cloud platform of your choice. Customize Watson to grasp the specific language of your business and pull tailored insights using Watson Knowledge Studio. Your data ownership is preserved, as we prioritize the security and confidentiality of your information, ensuring that IBM will neither collect nor store your data. By employing our sophisticated natural language processing (NLP) tools, developers are equipped to process and uncover valuable insights from their unstructured data, ultimately enhancing decision-making capabilities. This innovative approach not only streamlines data analysis but also empowers organizations to harness the full potential of their information assets.
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Google Cloud Natural Language API
Leverage advanced machine learning techniques for thorough text analysis that can extract, interpret, and securely store textual data. With AutoML, you can create top-tier custom machine learning models effortlessly, without writing any code. Implement natural language understanding through the Natural Language API to enhance your applications. Utilize entity analysis to pinpoint and categorize various fields in documents, such as emails, chats, and social media interactions, followed by sentiment analysis to gauge customer feedback and derive actionable insights for product improvements and user experience. The Natural Language API, combined with speech-to-text capabilities, can also provide valuable insights from audio sources. Additionally, the Vision API enhances your capabilities with optical character recognition (OCR) for digitizing scanned documents. The Translation API further enables sentiment understanding across diverse languages. With custom entity extraction, you can identify specialized entities within your documents that may not be recognized by standard models, saving both time and resources on manual processing. Ultimately, you can train your own high-quality machine learning models to effectively classify, extract, and assess sentiment, making your analysis more targeted and efficient. This comprehensive approach ensures a robust understanding of textual and audio data, empowering businesses with deeper insights.
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